Managing a sales team is hard. The role of the front-line line sales manager is the lynch-pin of most sales organizations, but the number of tasks that Sales Managers have to juggle makes it really difficult to know how to answer the questions “How do I get the most from my sales team?” and “How do I remove uncertainty?”

Just think about all of the tasks a sales manager has to balance … hiring, enablement, sales coaching, closing deals, running the sales forecast, managing the pipeline, supporting HQ information requests, and conducting the quarterly business reviews … and that’s when she is not traveling. Sales managers are encouraged to invest time in coaching to improve the team, or rely on sales analytics to help determine where to focus.

Even though coaching is recognized as being a true driver of sales productivity when implemented effectively, most sales managers don’t employ a consistent coaching practice in their business. In fact 73% of sales managers spend less than 5% of their time coaching.

Some don’t know how to coach, others don’t see the value and in many cases sales managers cite ‘Not enough time’ as a key reason for not engaging in this proven best practice. We think that in fact the real reason is that sales managers do not have the requisite knowledge that equips them to coach effectively and often can’t easily assess what opportunities or sellers would benefit from a coaching intervention.

The math explains this better. Let’s assume that the sales manager has eight people on her team, each working six material opportunities, and a ninety-day sales cycle. That’s 48 opportunities in her universe at any one time. Even if she tries to coach just half of these opportunities effectively each month, spending two hours per opportunity, she runs out of time pretty quickly. How is she to know where to focus? There has to be a way to triage both the opportunities and the sellers so that her time is applied where it has most impact. What matters gets lost in the volume of data or information to assimilate.

We know from studies by IBM and MIT that sales organizations are 10X more likely to be High Performers if they use analytics well. The problem however is that 55% of all analytics projects fail. Failure usually occurs because the scope of the project is too wide, there is little or no connection to business outcomes in the design of the project, and there is a deficit of business domain expertise in interpreting the analysis, linking correlations to causation and gaining actionable prescriptive insights. What matters get lost in the metrics.

Most approaches we have seen think about data to predict sales performance in three or four buckets: